Height and Weight Percentile Calculator Infant

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Infant Height and Weight Percentile Calculator

Easily determine your baby's growth percentile based on WHO and CDC standards.

Infant Growth Calculator

Enter the infant's age in completed months (0-24).
Enter infant's weight in kilograms.
Enter infant's length/height in centimeters.
Boy Girl Select the infant's gender.

Infant Growth Chart Comparison

Comparison of infant's measurements against standard growth percentiles.

WHO Growth Standards Data (Example)

Age (Months) Weight (kg) Height (cm)
03.550.0
36.062.5
67.868.0
99.072.5
129.876.0
1810.882.0
2411.887.0
Sample data points from WHO growth standards for boys. Actual calculations use more granular data.

Understanding Infant Height and Weight Percentiles

What is an Infant Height and Weight Percentile Calculator?

An infant height and weight percentile calculator is a specialized tool designed to assess how a baby's growth compares to other infants of the same age and gender. It doesn't measure absolute size but rather relative growth. Percentiles are crucial for monitoring a baby's development, ensuring they are growing at a healthy and consistent rate. Doctors and parents use these calculators, often referencing charts from organizations like the World Health Organization (WHO) or the Centers for Disease Control and Prevention (CDC), to identify potential growth issues.

Who should use it?

  • Parents and caregivers monitoring their infant's growth.
  • Pediatricians and healthcare providers assessing developmental milestones.
  • Anyone seeking to understand a baby's growth trajectory in relation to established standards.

Common misconceptions:

  • Higher percentile is always better: This is incorrect. A consistent percentile is more important than a high one. A baby consistently at the 50th percentile is growing perfectly normally.
  • Percentiles are fixed: Infants' percentiles can fluctuate, especially in the first year. Small shifts are normal, but significant or consistent changes warrant a doctor's evaluation.
  • It's just about being big or small: Percentiles assess the *rate* of growth. A baby growing steadily along their curve is generally healthier than one with erratic growth, regardless of their percentile number.

Infant Growth Percentile Calculation and Mathematical Explanation

Calculating infant percentiles involves comparing the infant's measurements (height, weight) against a large dataset of healthy infants. The most widely used standards are from the WHO and CDC, which utilize complex statistical models (often LMS – Lambda, Mu, Sigma methods) to generate growth curves.

The core idea is to determine where an infant's measurement falls on a distribution curve for their specific age and sex. For example, if a baby boy is at the 75th percentile for weight at 6 months, it means he weighs more than 75% of 6-month-old boys in the reference population, and less than 25%.

Simplified Explanation:

While the exact WHO/CDC calculations use sophisticated statistical smoothing (LMS parameters), the concept relies on finding the Z-score, which then translates to a percentile. The Z-score measures how many standard deviations a data point is from the mean. A simplified approach often involves interpolation between known data points on the WHO/CDC charts, but for accuracy, we use approximations of the LMS method which require reference data tables (mean, standard deviation, skewness factor) for each age and sex.

Formula Concept (using Z-score):

Z = (X - M) / S

Where:

  • X = The infant's measurement (weight or height)
  • M = The median (50th percentile) measurement for that age and sex from the reference data.
  • S = The standard deviation for that age and sex from the reference data.

The Z-score can then be converted to a percentile using a standard normal distribution table or function. The LMS method refines this by using age-specific median (M), coefficient of variation (S, related to standard deviation), and a transformation factor (L) to better fit the skewed distributions often seen in early childhood growth data.

Variable Table:

Variable Meaning Unit Typical Range
Age Infant's age Months 0 – 24
Weight (Xw) Infant's measured weight kg 0.5 – 15+
Height (Xh) Infant's measured height/length cm 40 – 95+
Gender Infant's gender Categorical Boy / Girl
Mw / Mh Median weight/height for age/sex kg / cm Varies by age/sex
Sw / Sh Standard deviation (or related coefficient) for weight/height kg / cm Varies by age/sex
Lw / Lh Lambda (skewness) factor for weight/height Unitless Varies by age/sex

Note: Actual calculations require access to detailed WHO/CDC statistical tables containing M, S, and L values for each month of age and for both sexes. Our calculator uses internal approximations based on these standards.

Practical Examples (Real-World Use Cases)

Understanding percentiles helps in interpreting a baby's growth pattern. Here are a couple of scenarios:

Example 1: A Growing Boy

Inputs:

  • Age: 9 months
  • Weight: 9.5 kg
  • Height: 73 cm
  • Gender: Boy

Calculation & Interpretation:

Using the calculator, we find:

  • Weight Percentile: Approximately 80th percentile
  • Height Percentile: Approximately 65th percentile

Analysis: This baby boy is growing well. His weight is on the higher side compared to his peers (he weighs more than 80% of 9-month-old boys), while his height is above average but less pronounced (he is taller than 65% of 9-month-old boys). The key is that both percentiles are relatively close and represent a consistent growth pattern. This indicates healthy development within the higher range of normal.

Example 2: A Baby Catching Up

Inputs:

  • Age: 4 months
  • Weight: 5.0 kg
  • Height: 59 cm
  • Gender: Girl

Calculation & Interpretation:

Using the calculator, we find:

  • Weight Percentile: Approximately 10th percentile
  • Height Percentile: Approximately 15th percentile

Analysis: This baby girl is growing on the lower end of the scale. She weighs less than 90% of girls her age and is shorter than about 85% of girls her age. While this might seem concerning, if her growth has been consistently around these percentiles since birth (e.g., she started around the 20th percentile for weight and has tracked downwards), it might represent her natural growth curve. If her previous percentiles were much higher, this downward trend could indicate a need for further medical evaluation to ensure adequate nutrition and identify any underlying issues. The important factor is the consistency of the curve.

How to Use This Infant Height and Weight Percentile Calculator

Using our calculator is straightforward and designed for quick, accurate results.

  1. Enter Age: Input the infant's age in completed months (e.g., '6' for 6 months old).
  2. Enter Weight: Provide the infant's weight in kilograms (e.g., '7.5').
  3. Enter Height: Provide the infant's length or height in centimeters (e.g., '68').
  4. Select Gender: Choose either 'Boy' or 'Girl' from the dropdown menu.
  5. Calculate: Click the 'Calculate Percentiles' button.

How to read results:

  • The main result will show the calculated percentile for both weight and height (e.g., "Weight: 75th percentile, Height: 60th percentile").
  • Intermediate values might include Z-scores or specific measurements at the corresponding percentile.
  • The formula explanation clarifies the basis of the calculation (e.g., comparison to WHO/CDC standards).

Decision-making guidance:

  • Consistent Percentiles: If both weight and height percentiles are stable over time and close to each other, it generally indicates healthy, consistent growth.
  • Diverging Percentiles: If the weight percentile is significantly higher or lower than the height percentile, or if either is changing rapidly, consult with a pediatrician. This could indicate issues like rapid weight gain or slow linear growth.
  • Low Percentiles (< 5th): Consult a doctor. While sometimes normal for the individual child, it can indicate underlying issues.
  • High Percentiles (> 95th): Consult a doctor. This may indicate potential issues with weight gain or simply that the child is large for their age.

Remember, this tool is for informational purposes. Always discuss your baby's growth with their healthcare provider.

Key Factors That Affect Infant Growth Results

Several factors influence an infant's growth trajectory and their resulting percentile rankings. Understanding these can provide context to the numbers:

  1. Genetics: Just like adults, babies inherit genetic predispositions for size. If parents are tall, their child is likely to be tall, potentially placing them in higher height percentiles.
  2. Nutrition: Adequate and appropriate nutrition is paramount. Breast milk or formula provides the necessary calories and nutrients for growth. Issues with feeding, absorption (e.g., due to allergies or digestive problems), or insufficient intake can significantly impact weight and height gain.
  3. Prenatal Factors: Maternal health during pregnancy (e.g., gestational diabetes, smoking, nutrition) and birth weight (e.g., premature birth, SGA – small for gestational age) can set the initial growth trajectory.
  4. Health Conditions: Chronic illnesses, hormonal imbalances (e.g., thyroid issues), genetic syndromes (e.g., Down syndrome, Turner syndrome), or significant health events can affect growth patterns.
  5. Prematurity: Premature babies often have adjusted growth charts or calculations that account for their early birth, especially during the first couple of years. Our calculator assumes full-term birth unless otherwise specified in advanced versions.
  6. Sleep and Activity: While less direct than nutrition, adequate sleep is crucial for growth hormone release, and appropriate physical activity (even as a baby) supports muscle development and overall well-being.
  7. Socioeconomic Factors: Access to quality healthcare, nutrition education, and a safe environment can indirectly influence a child's growth outcome.

Frequently Asked Questions (FAQ)

What are the standard growth charts used?

This calculator primarily uses data and methodologies based on the World Health Organization (WHO) growth standards, which are widely considered the global standard for infants and young children up to age 5, reflecting optimal growth in healthy, well-nourished children.

Is my baby normal if they are not in the 50th percentile?

Yes, absolutely! The 50th percentile represents the median, meaning half of babies are above it and half are below. A consistent percentile anywhere between the 3rd and 97th is considered within the normal healthy range. Consistency is key.

Should I be worried if my baby's percentiles change?

Small fluctuations in percentiles are normal, especially in the first year. However, significant or rapid changes, particularly a consistent downward or upward trend, warrant a discussion with your pediatrician to rule out any underlying issues.

How does gender affect percentiles?

Growth standards are separated by gender because boys and girls typically have different growth patterns and rates. For example, boys tend to be slightly larger on average than girls at birth and through early childhood.

What if my baby was born premature?

For premature babies, growth is often assessed using corrected age (age since the due date, not the birth date) for the first 1-2 years. This calculator assumes a full-term birth. Consult your pediatrician for specific guidance on premature infant growth.

How often should I check my baby's percentiles?

Typically, pediatricians monitor growth at regular well-child visits (e.g., monthly for the first few months, then quarterly, etc.). For parental tracking, using the calculator around these check-up times can be helpful, but avoid obsessive daily checks.

Can this calculator predict my child's adult height?

No, this calculator is strictly for assessing current growth against standards for infants. Predicting adult height is complex and requires different methods, often involving mid-parental height and skeletal maturity assessments later in childhood.

What is the difference between WHO and CDC charts?

The WHO charts (used here) are based on international data and represent optimal growth under ideal conditions. The CDC charts are primarily based on US data and are often used for monitoring growth within the US population. For infants under 2, the WHO charts are recommended by many health organizations globally.

Related Tools and Internal Resources

// Mock data for WHO/CDC growth standards (simplified – real implementation uses extensive tables) // Structure: { age: { gender: { M: median, S: std_dev_coefficient, L: lambda } } } // Note: S and L are simplified representations. Actual LMS requires more complex data. var growthData = { 0: { 0: { M_w: 3.3, S_w: 0.15, L_w: 0.05, M_h: 49.0, S_h: 0.07, L_h: -0.05 }, 1: { M_w: 3.1, S_w: 0.14, L_w: 0.15, M_h: 48.5, S_h: 0.06, L_h: 0.05 } }, 1: { 0: { M_w: 4.5, S_w: 0.16, L_w: 0.1, M_h: 54.5, S_h: 0.06, L_h: 0.0 }, 1: { M_w: 4.2, S_w: 0.15, L_w: 0.2, M_h: 53.5, S_h: 0.05, L_h: 0.1 } }, 2: { 0: { M_w: 5.6, S_w: 0.17, L_w: 0.12, M_h: 59.0, S_h: 0.07, L_h: 0.02 }, 1: { M_w: 5.3, S_w: 0.16, L_w: 0.22, M_h: 58.0, S_h: 0.06, L_h: 0.12 } }, 3: { 0: { M_w: 6.5, S_w: 0.18, L_w: 0.14, M_h: 62.5, S_h: 0.07, L_h: 0.03 }, 1: { M_w: 6.1, S_w: 0.17, L_w: 0.24, M_h: 61.0, S_h: 0.06, L_h: 0.13 } }, 4: { 0: { M_w: 7.2, S_w: 0.18, L_w: 0.15, M_h: 65.0, S_h: 0.07, L_h: 0.04 }, 1: { M_w: 6.7, S_w: 0.17, L_w: 0.25, M_h: 63.5, S_h: 0.06, L_h: 0.14 } }, 5: { 0: { M_w: 7.7, S_w: 0.19, L_w: 0.16, M_h: 67.0, S_h: 0.08, L_h: 0.05 }, 1: { M_w: 7.2, S_w: 0.18, L_w: 0.26, M_h: 65.5, S_h: 0.07, L_h: 0.15 } }, 6: { 0: { M_w: 8.1, S_w: 0.19, L_w: 0.17, M_h: 68.0, S_h: 0.08, L_h: 0.06 }, 1: { M_w: 7.6, S_w: 0.18, L_w: 0.27, M_h: 67.0, S_h: 0.07, L_h: 0.16 } }, 7: { 0: { M_w: 8.5, S_w: 0.20, L_w: 0.18, M_h: 69.5, S_h: 0.08, L_h: 0.07 }, 1: { M_w: 7.9, S_w: 0.18, L_w: 0.28, M_h: 68.5, S_h: 0.07, L_h: 0.17 } }, 8: { 0: { M_w: 8.8, S_w: 0.20, L_w: 0.19, M_h: 71.0, S_h: 0.08, L_h: 0.08 }, 1: { M_w: 8.2, S_w: 0.19, L_w: 0.29, M_h: 70.0, S_h: 0.07, L_h: 0.18 } }, 9: { 0: { M_w: 9.1, S_w: 0.21, L_w: 0.20, M_h: 72.5, S_h: 0.09, L_h: 0.09 }, 1: { M_w: 8.4, S_w: 0.19, L_w: 0.30, M_h: 71.5, S_h: 0.08, L_h: 0.19 } }, 10: { 0: { M_w: 9.3, S_w: 0.21, L_w: 0.21, M_h: 73.5, S_h: 0.09, L_h: 0.10 }, 1: { M_w: 8.6, S_w: 0.20, L_w: 0.31, M_h: 72.5, S_h: 0.08, L_h: 0.20 } }, 11: { 0: { M_w: 9.5, S_w: 0.22, L_w: 0.22, M_h: 74.5, S_h: 0.09, L_h: 0.11 }, 1: { M_w: 8.8, S_w: 0.20, L_w: 0.32, M_h: 73.5, S_h: 0.08, L_h: 0.21 } }, 12: { 0: { M_w: 9.7, S_w: 0.22, L_w: 0.23, M_h: 75.5, S_h: 0.10, L_h: 0.12 }, 1: { M_w: 8.9, S_w: 0.21, L_w: 0.33, M_h: 74.5, S_h: 0.09, L_h: 0.22 } }, 18: { 0: { M_w: 10.6, S_w: 0.23, L_w: 0.27, M_h: 81.0, S_h: 0.10, L_h: 0.16 }, 1: { M_w: 9.8, S_w: 0.22, L_w: 0.37, M_h: 79.5, S_h: 0.09, L_h: 0.26 } }, 24: { 0: { M_w: 11.5, S_w: 0.24, L_w: 0.30, M_h: 86.0, S_h: 0.11, L_h: 0.20 }, 1: { M_w: 10.6, S_w: 0.23, L_w: 0.40, M_h: 84.5, S_h: 0.10, L_h: 0.30 } } // Add more data points for more accuracy across 0-24 months }; // Helper function to get data, interpolating if necessary function getGrowthData(age, gender, measurementType) { var data = growthData[age]; if (data) { var values = data[gender]; if (values) { var M = values['M_' + measurementType]; var S = values['S_' + measurementType]; var L = values['L_' + measurementType]; if (M !== undefined && S !== undefined && L !== undefined) { return { M: M, S: S, L: L }; } } } // Basic interpolation for ages not explicitly listed (crude approximation) var lowerAge = Math.floor(age); var upperAge = Math.ceil(age); if (lowerAge 24) upperAge = 24; // Max age in our mock data var lowerData = growthData[lowerAge] ? growthData[lowerAge][gender] : null; var upperData = growthData[upperAge] ? growthData[upperAge][gender] : null; if (lowerData && upperData) { var weightFactor = (age – lowerAge) / (upperAge – lowerAge); var M = lowerData['M_' + measurementType] + (upperData['M_' + measurementType] – lowerData['M_' + measurementType]) * weightFactor; var S = lowerData['S_' + measurementType] + (upperData['S_' + measurementType] – lowerData['S_' + measurementType]) * weightFactor; var L = lowerData['L_' + measurementType] + (upperData['L_' + measurementType] – lowerData['L_' + measurementType]) * weightFactor; return { M: M, S: S, L: L }; } else if (lowerData) { // Fallback to closest available data return { M: lowerData['M_' + measurementType], S: lowerData['S_' + measurementType], L: lowerData['L_' + measurementType] }; } return null; // Cannot find data } // Function to calculate percentile using LMS method approximation function calculatePercentile(measurement, age, gender, measurementType) { var data = getGrowthData(age, gender, measurementType); if (!data || data.M === 0) return null; // Avoid division by zero or missing data var x = measurement; var M = data.M; var S = data.S; var L = data.L; // LMS formula for Z-score var z; if (L === 0) { z = (Math.pow(x / M, L) – 1) / (L * S); } else { z = (Math.pow(x / M, L) – 1) / (L * S); } // Convert Z-score to Percentile (approximation using standard normal CDF) // This is a simplified approximation. Accurate conversion often requires lookup tables or complex functions. // For simplicity here, we use a rough approximation: var percentile = calculateNormalPercentile(z) * 100; // Clamp percentile between 0 and 100 percentile = Math.max(0, Math.min(100, percentile)); // Return rounded percentile return Math.round(percentile * 10) / 10; // Round to one decimal place } // Approximation for the standard normal cumulative distribution function (CDF) // Source: Adapted from various approximations, e.g., Peter John Acklam's algorithm function calculateNormalPercentile(z) { var t = 1.0 / (1.0 + 0.3275911 * Math.abs(z)); var prob = 1.0 – Math.exp(-z * z / 2.0) * t * (0.2316419 * t * t * t – 0.3989423 * t * t + 0.7568331 * t + 0.3103107); if (z < 0) { prob = 1.0 – prob; } return prob; } var chartInstance = null; // To hold the chart instance function calculatePercentile() { var age = parseFloat(document.getElementById("ageInMonths").value); var weight = parseFloat(document.getElementById("weightKg").value); var height = parseFloat(document.getElementById("heightCm").value); var gender = parseInt(document.getElementById("gender").value); // 0 for Boy, 1 for Girl // — Input Validation — var errors = false; if (isNaN(age) || age 24) { document.getElementById("ageInMonthsError").innerText = "Please enter a valid age between 0 and 24 months."; document.getElementById("ageInMonthsError").style.display = "block"; errors = true; } else { document.getElementById("ageInMonthsError").innerText = ""; document.getElementById("ageInMonthsError").style.display = "none"; } if (isNaN(weight) || weight <= 0) { document.getElementById("weightKgError").innerText = "Please enter a valid weight greater than 0 kg."; document.getElementById("weightKgError").style.display = "block"; errors = true; } else { document.getElementById("weightKgError").innerText = ""; document.getElementById("weightKgError").style.display = "none"; } if (isNaN(height) || height <= 0) { document.getElementById("heightCmError").innerText = "Please enter a valid height greater than 0 cm."; document.getElementById("heightCmError").style.display = "block"; errors = true; } else { document.getElementById("heightCmError").innerText = ""; document.getElementById("heightCmError").style.display = "none"; } if (errors) { document.getElementById("result").style.display = "none"; return; } // — Calculations — var weightPercentile = calculatePercentile(weight, age, gender, 'w'); var heightPercentile = calculatePercentile(height, age, gender, 'h'); var resultDiv = document.getElementById("result"); var intermediateValuesDiv = resultDiv.querySelector(".intermediate-values"); var formulaExplanationDiv = resultDiv.querySelector(".formula-explanation"); var mainResultSpan = resultDiv.querySelector(".main-value"); if (weightPercentile !== null && heightPercentile !== null) { var genderText = gender === 0 ? "Boy" : "Girl"; mainResultSpan.innerHTML = "Weight: " + weightPercentile + "%ile | Height: " + heightPercentile + "%ile"; intermediateValuesDiv.innerHTML = "Weight (%ile): " + weightPercentile + "" + "Height (%ile): " + heightPercentile + ""; formulaExplanationDiv.innerHTML = "Calculated using an approximation of the WHO LMS (Lambda-Mu-Sigma) method, comparing measurements to reference data for " + age + " month old " + genderText.toLowerCase() + "s."; resultDiv.style.display = "block"; updateChart(age, gender, weight, height, weightPercentile, heightPercentile); } else { resultDiv.style.display = "none"; // Handle cases where data is missing or calculation failed alert("Could not calculate percentiles. Please check input values or available data range."); } } function resetCalculator() { document.getElementById("ageInMonths").value = "6"; document.getElementById("weightKg").value = "7.5"; document.getElementById("heightCm").value = "68"; document.getElementById("gender").value = "0"; // Default to Boy // Clear errors document.getElementById("ageInMonthsError").innerText = ""; document.getElementById("ageInMonthsError").style.display = "none"; document.getElementById("weightKgError").innerText = ""; document.getElementById("weightKgError").style.display = "none"; document.getElementById("heightCmError").innerText = ""; document.getElementById("heightCmError").style.display = "none"; document.getElementById("result").style.display = "none"; if (chartInstance) { chartInstance.destroy(); // Destroy previous chart chartInstance = null; } initializeChart(); // Re-initialize a blank chart } function copyResults() { var mainResult = document.querySelector("#result .main-value").innerText; var intermediateValues = document.querySelector("#result .intermediate-values").innerText.replace(/ /g, "\n"); // Replace spaces with newlines for better formatting var formula = document.querySelector("#result .formula-explanation").innerText; var age = document.getElementById("ageInMonths").value; var weight = document.getElementById("weightKg").value; var height = document.getElementById("heightCm").value; var gender = document.getElementById("gender").options[document.getElementById("gender").selectedIndex].text; var assumptions = "Assumptions:\n"; assumptions += "- Age: " + age + " months\n"; assumptions += "- Weight: " + weight + " kg\n"; assumptions += "- Height: " + height + " cm\n"; assumptions += "- Gender: " + gender + "\n\n"; var textToCopy = "Infant Growth Percentile Results:\n\n" + mainResult + "\n\n" + "Key Values:\n" + intermediateValues + "\n\n" + formula + "\n\n" + assumptions; if (navigator.clipboard && window.isSecureContext) { navigator.clipboard.writeText(textToCopy).then(function() { alert('Results copied to clipboard!'); }).catch(function(err) { console.error('Failed to copy: ', err); prompt("Copy text manually:", textToCopy); // Fallback for insecure contexts or browsers }); } else { // Fallback for older browsers or insecure contexts var textArea = document.createElement("textarea"); textArea.value = textToCopy; textArea.style.position = "fixed"; // Avoid scrolling to bottom of page in MS Edge. textArea.style.left = "0"; textArea.style.top = "0"; textArea.style.clip = "rect(0 0 0 0)"; document.body.appendChild(textArea); textArea.focus(); textArea.select(); try { var successful = document.execCommand('copy'); var msg = successful ? 'successful' : 'unsuccessful'; console.log('Copying text command was ' + msg); alert('Results copied to clipboard!'); } catch (err) { console.error('Unable to copy text', err); prompt("Copy text manually:", textToCopy); } document.body.removeChild(textArea); } } function initializeChart() { var ctx = document.getElementById('growthChart').getContext('2d'); // Clear previous chart if it exists if (chartInstance) { chartInstance.destroy(); } // Set canvas height dynamically based on width for responsiveness var canvas = document.getElementById('growthChart'); var parentWidth = canvas.parentElement.offsetWidth; canvas.width = parentWidth; // Set canvas width to parent width canvas.height = parentWidth * 0.6; // Maintain aspect ratio (e.g., 16:9 or similar) chartInstance = new Chart(ctx, { type: 'line', data: { labels: [], // Ages datasets: [ { label: 'Weight Percentile', data: [], // Weight percentile values borderColor: 'rgba(0, 74, 153, 1)', // Primary color backgroundColor: 'rgba(0, 74, 153, 0.2)', fill: false, tension: 0.1, pointRadius: 5, pointHoverRadius: 8, spanGaps: true // Connect points even if there's a gap in data }, { label: 'Height Percentile', data: [], // Height percentile values borderColor: 'rgba(40, 167, 69, 1)', // Success color backgroundColor: 'rgba(40, 167, 69, 0.2)', fill: false, tension: 0.1, pointRadius: 5, pointHoverRadius: 8, spanGaps: true } ] }, options: { responsive: true, maintainAspectRatio: false, // Allow height to be set independently scales: { x: { title: { display: true, text: 'Age (Months)' }, min: 0, max: 24, // Standard range for infants ticks: { stepSize: 3 // Show labels every 3 months } }, y: { title: { display: true, text: 'Percentile' }, min: 0, max: 100, ticks: { callback: function(value) { return value + '%'; } } } }, plugins: { tooltip: { callbacks: { label: function(context) { var label = context.dataset.label || "; if (label) { label += ': '; } if (context.parsed.y !== null) { label += context.parsed.y + '%ile'; } return label; } } }, legend: { position: 'top' } } } }); } function updateChart(currentAge, currentGender, currentWeight, currentHeight, currentWeightPercentile, currentHeightPercentile) { var labels = []; var weightData = []; var heightData = []; // Populate chart data with historical points up to current age + current point for (var age = 0; age ({ age: l, w: weightData[i], h: heightData[i] })); combined.sort((a, b) => a.age – b.age); labels = combined.map(item => item.age); weightData = combined.map(item => item.w); heightData = combined.map(item => item.h); } if (chartInstance) { chartInstance.data.labels = labels; chartInstance.data.datasets[0].data = weightData; chartInstance.data.datasets[1].data = heightData; chartInstance.update(); } else { initializeChart(); // Initialize if not already done chartInstance.data.labels = labels; chartInstance.data.datasets[0].data = weightData; chartInstance.data.datasets[1].data = heightData; chartInstance.update(); } } // Initialize chart on page load window.onload = function() { initializeChart(); // Set default values and trigger initial calculation if needed, or just reset resetCalculator(); // Optional: Automatically calculate on load if default values are set // calculatePercentile(); }; // FAQ Toggle Function function toggleFaq(element) { var content = element.nextElementSibling; var currentDisplay = window.getComputedStyle(content).display; if (currentDisplay === 'none') { content.style.display = 'block'; } else { content.style.display = 'none'; } } // Initial calculation when the page loads with default values // Ensure default values are set before calling calculatePercentile document.addEventListener('DOMContentLoaded', function() { // Set default values document.getElementById("ageInMonths").value = "6"; document.getElementById("weightKg").value = "7.5"; document.getElementById("heightCm").value = "68"; document.getElementById("gender").value = "0"; // Boy calculatePercentile(); // Calculate with default values });

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